Agam Iheanyi‑Igwe

About

CS student at Stanford, passionate about mitigating algorithmic bias and building impactful software.

Education

Stanford University — Bachelor's, Computer Science (2023–2027). Grade: 3.84/4.0

Relevant coursework: CS161, CS107, CS109, CS106B, CS103, CS124, CS111, CS29N

Howard Community College — Associates in STEM Studies (2019–2023). GPA: 3.89/4.0

Experience

LinkedIn Corporation — Software & Product Engineering Intern (Summer 2025)

  • Built tier selection system using statistical analysis to segment users by spending patterns and budget constraints, contributing to significant revenue increase through optimized pricing algorithms.
  • Developing low-latency backend services to improve system throughput for high-volume tier decisions, leveraging data-driven classification models to enhance targeting precision.

Stanford University Department of Computer Science — Undergraduate Teaching Assistant (Winter 2024 – Present)

  • Teach weekly sections and host office hours for Stanford’s introductory data structures and algorithms course, supporting 900+ students in mastering core Python and C++ concepts.
  • Collaborate with professors and teaching staff to design and refine lesson plans, assignments, and exams, ensuring alignment with course objectives and fostering student success.

Amazon.com, Inc. — Software Development Intern (Summer 2024)

  • Eliminated 6-hour processing delays for on-call engineers using AWS tools to optimize workflows for large customer orders, reducing manual interventions to near-zero.
  • Achieved 20% increase in large-order processing efficiency, reaching 100% customer deployment in all Prod regions and demonstrating extensibility within Amazon’s backend codebase.

Jane Street — AMP Fellow (Summer 2023)

  • Completed a selective five-week program training in quantitative trading: probability, statistics, game theory, combinatorics, number theory, and programming.
  • Generated mock ETFs, identified key stakeholders, resolved creation-related challenges, and developed market and analytical abilities.

Skills

Projects

AskDolph (Summer 2025)

  • AI relationship assistant using sentiment analysis and voice synthesis with persistent memory to analyze communication patterns across text, voice, and social media interactions.
  • Provides personalized relationship advice and compatibility assessments (currently in closed beta).

CAMP (Spring 2025)

  • Built backend infrastructure for Howard University social platform (260+ beta users) using Node.js/Express and WebSocket servers.
  • Enabled real-time messaging, event discovery, and marketplace functionality.

Tools

Campus Involvement

Interests & Hobbies